Like high-frequency traders on Wall Street, a growing army of bots exploit inefficiencies in decentralized exchanges, which are places where users buy, sell or trade cryptocurrency independent of a central authority, a new study found. The researchers also found that high fees paid to prioritize certain transactions pose a security threat to the entire blockchain.

The reality is not so simple, according to new Cornell Tech research.

Like high-frequency traders on Wall Street, a growing army of bots exploit inefficiencies in decentralized exchanges, which are places where users buy, sell or trade cryptocurrency independent of a central authority, the study found. The researchers also found that high fees paid to prioritize certain transactions pose a security threat to the entire blockchain.

These practices allow predatory users to anticipate and profit from everyday trades, siphoning millions or possibly billions of dollars a year in cryptocurrency.

«In a traditional system you have a broker or someone you’re trading through, and you trust them, or they’re legally required to do the right thing,» said Philip Daian, Cornell Tech doctoral student in computer science and first author of «Flash Boys 2.0: Frontrunning, Transaction Reordering and Consensus Instability in Decentralized Exchanges,» which was presented at the Cornell Blockchain Conference April 13 at Cornell Tech.

«In these systems, the broker is replaced by the blockchain, which seems like a trusted third party, but in reality there are a lot of different moving parts in the blockchain that can be manipulated,» he said. «So you have to be very careful about what the blockchain is actually giving you.»

To conduct the study, an eight-person team led by Ari Juels, professor of computer science at the Jacobs Technion-Cornell Institute at Cornell Tech and senior author of the paper, spent 18 months tracking trades on six decentralized exchanges. They then measured when they heard about the transactions, who reported them and at what time.

Story Source: Materials provided by Cornell University. Original written by Melanie Lefkowitz. Note: Content may be edited for style and length.